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» Mobile learning: A framework and evaluation
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IS
2008
13 years 9 months ago
Mining relational data from text: From strictly supervised to weakly supervised learning
This paper approaches the relation classification problem in information extraction framework with different machine learning strategies, from strictly supervised to weakly superv...
Zhu Zhang
ICSE
2012
IEEE-ACM
11 years 11 months ago
Recovering traceability links between an API and its learning resources
—Large frameworks and libraries require extensive developer learning resources, such as documentation and mailing lists, to be useful. Maintaining these learning resources is cha...
Barthélémy Dagenais, Martin P. Robil...
PERVASIVE
2008
Springer
13 years 9 months ago
AnonySense: Opportunistic and Privacy-Preserving Context Collection
Opportunistic sensing allows applications to "task" mobile devices to measure context in a target region. For example, one could leverage sensorequipped vehicles to measu...
Apu Kapadia, Nikos Triandopoulos, Cory Cornelius, ...
ICONIP
2009
13 years 6 months ago
Tracking in Reinforcement Learning
Reinforcement learning induces non-stationarity at several levels. Adaptation to non-stationary environments is of course a desired feature of a fair RL algorithm. Yet, even if the...
Matthieu Geist, Olivier Pietquin, Gabriel Fricout
ICWL
2009
Springer
14 years 3 months ago
Social Reference Model for Adaptive Web Learning
In this paper, we describe the design steps of extending LAOS, a five-layer framework for generic adaptive web learning authoring, by adding a social layer to capture (and adapt) i...
Fawaz Ghali, Alexandra I. Cristea